pharmacokinetics and metabolism in drug design

1.2 Partition and Distribution Coefficient as Measures of Lipophilicity 21.4.1 Unravelling the Principal Contributions to log P 6 1.5 Alternative Lipophilicity Scales 8 2 Pharmacokinetic

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Pharmacokinetics and Metabolism

in Drug Design

by Dennis A Smith, Han van de Waterbeemd and Don K Walker

Pharmacokinetics and Metabolism in Drug Design

Edited by D A Smith, H van de Waterbeemd, D K Walker, R Mannhold, H Kubinyi, H Timmerman

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Methods and Principles

G Folkers, H.-D Höltje, J.Vacca,

H van de Waterbeemd, T Wieland

Edited by D A Smith, H van de Waterbeemd, D K Walker,

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Weinheim – New-York – Chichester – Brisbane – Singapore – Toronto

by Dennis A.Smith,

Han van de Waterbeemd

and Don K.Walker

Pharmacokinetics and Metabolism

in Drug Design

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Series Editors:

Prof Dr Raimund Mannhold

Biomedical Research Center

Molecular Drug Research Group

Library of Congress Card No.:

applied for

British Library Cataloguing-in-Publication Data

A catalogue record for this book is available from the British Library.

Die Deutsche Bibliothek – CIP in-Publication Data

Cataloguing-A catalogue record for this publication is available from Die Deutsche Bibliothek

No part of this book may be reproduced

in any form – by photoprinting, film, or any other means – nor transmitted

micro-or translated into a machine language without written permission from the publishers.

Printed in the Federal Republic of Germany Printed on acid-free paper

Cover Design Gunther Schulz, Fußgönnheim

Typesetting TypoDesign Hecker GmbH, Leimen

Printing Strauss Offsetdruck, Mörlenbach

Binding Osswald & Co., Neustadt (Weinstraße)

ISBN 3-527-30197-6

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1.2 Partition and Distribution Coefficient as Measures of Lipophilicity 2

1.4.1 Unravelling the Principal Contributions to log P 6

1.5 Alternative Lipophilicity Scales 8

2 Pharmacokinetics 15

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5 Clearance 59

6 Renal Clearance 67

7 Metabolic (Hepatic) Clearance 75

7.2.1 Catalytic Selectivity of CYP2D6 78

7.2.2 Catalytic Selectivity of CYP2C9 80

7.2.3 Catalytic Selectivity of CYP3A4 81

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Contents VII

9.4 Species Scaling: Incorporating Differences in Metabolic Clearance 128

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VIII Contents

Index 143

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Preface

The present volume of the series Methods and Principles in Medicinal Chemistry

focuses on the impact of pharmacokinetics and metabolism in Drug Design macokinetics is the study of the kinetics of absorption, distribution, metabolism, andexcretion of drugs and their pharmacologic, therapeutic, or toxic response in animalsand man

Phar-In the last 10 years drug discovery has changed rapidly Combinatorial chemistryand high-throughput screening have been introduced widely and now form the core

of the Discovery organizations of major pharmaceutical and many small biotechcompanies However, the hurdles between a hit, a lead, a clinical candidate, and asuccessful drug can be enormous

The main reasons for attrition during development include pharmacokinetics andtoxicity Common to both is drug metabolism The science of drug metabolism hasdeveloped over the last 30 years from a purely supporting activity trying to make thebest out of a development compound, to a mature partner in drug discovery Drugmetabolism departments are now working closely together with project teams to dis-cover well-balanced clinical candidates with a good chance of survival during devel-opment

The present volume draws on the long career in drug metabolism and experience

in the pharmaceutical industry of Dennis Smith Together with his colleagues Hanvan de Waterbeemd and Don Walker, all key issues in pharmacokinetics and drugmetabolism, including molecular toxicology have been covered, making the medici-nal chemist feel at home with this highly important topic

After a short introduction on physicochemistry, a number of chapters deal withpharmacokinetics, absorption, distribution, and clearance Metabolism and toxicityare discussed in depth In a further chapter species differences are compared and in-ter-species scaling is introduced The final chapter deals with high(er) throughputADME studies, the most recent trend to keep pace with similar paradigms in otherareas of the industry, such as chemistry

This book is a reflection of today's knowledge in drug metabolism and kinetics However, there is more to come, when in the future the role and function

pharmaco-of various transporters is better understood and predictive methods have maturedfurther

As series editors we would like to thank the authors for their efforts in bringingthis book to completion No doubt the rich experience of the authors expressed in

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X Preface

this volume will be of great value to many medicinal chemists, experienced or junior,and this volume will be a treasure in many laboratories engaged in the synthesis ofdrugs

Last, but not least we wish to express our gratitude to Gudrun Walter and FrankWeinreich from Wiley-VCH publishers for the fruitful collaboration

Hugo Kubinyi, LudwigshafenHenk Timmerman, Amsterdam

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A Personal Foreword

The concept of this book is simple It represents the distillation of my experiencesover 25 years within Drug Discovery and Drug Development and particularly howthe science of Drug Metabolism and Pharmacokinetics impacts upon MedicinalChemistry Hopefully it will be a source of some knowledge, but more importantly, astimulus for medicinal chemists to want to understand as much as possible aboutthe chemicals they make As the work grew I realized it was impossible to fulfil theconcept of this book without involving others I am extremely grateful to my co-au-thors Don Walker and Han van de Waterbeemd for helping turn a skeleton into afully clothed body, and in the process contributing a large number of new ideas anddirections Upon completion of the book I realize how little we know and how muchthere is to do Medicinal chemists often refer to the ‘magic methyl’ This term coversthe small synthetic addition, which almost magically solves a Discovery problem,transforming a mere ligand into a potential drug, beyond the scope of existing struc-ture–activity relationships A single methyl can disrupt crystal lattices, break hydra-tion spheres, modulate metabolism, enhance chemical stability, displace water in abinding site and turns the sometimes weary predictable plod of methyl, ethyl, propyl,futile into methyl, ethyl, another methyl magic! This book has no magical secrets un-fortunately, but time and time again the logical search for solutions is eventually re-warded by unexpected gains

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antimuscarinic compounds 87antipyrine 128

aplastic anaemia 103, 111aqueous channels 28, 29hydrophilic compounds 29aqueous pore 47, 64aqueous pores (tight junctions) 38atenolol 27, 50, 51, 64, 107azithromycin 54

b

β1/β2 selectivity 51β2-adrenergic receptor 30β-adrenoceptor antagonists 39, 64β-adrenoceptor blockers 86benzoquinone 104benzylic hydroxylation 83benzylic positions 83beta-adrenoceptor antagonist 42betaxolol 42, 79

biliary cannaliculus 102biliary clearance 60biliary excretion 60, 130bioavailability 22, 23, 41, 42bioisosteres 94

biophase 27blood dyscrasias 114blood flow 126blood-brain barrier 27, 28, 29, 50, 71body weight 124

bosentan 129brain weight 128

c

caco-2 44caco-2 cells 43caco-2 monolayers 3, 137calcium channel blockers 54

Index

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CYP2D6 32, 78basic nitrogen 78catalytic selectivity 78substrate-protein interaction 78template models 78

CYP3A4 41, 44, 81, 117, 119access channel 81active site 81SAR 81selectivity 81cytochrome 61cytochrome P450 32, 41, 62, 75, 76, 77, 104,

110, 112, 114, 117, 138chemistry 76reactive species 77

3 D-structure 77cytotoxic 110

d

danazole 37dealkylation 77deprotonation 91, 92DEREK 116, 138desipramine 49desolvation 39

D-glucuronic acid 90diclofenac 81, 105diflunisal 116dihydropyridine 54diltiazem 84disease states 124disease 71disobutamide 55disopyramide 55dissociation constant 26, 29dissolution 36, 65, 136rate of dissolution 36solubility 36surface area 36distal tubule 67distribution coefficient 4, 5degree of ionization 4diprotic molecules 5Henderson-Hasselbalch relationship 4monoprotic organic acids 4

monoprotic organic bases 4distribution 47, 65

DNA microarrays 116dofetilide 22

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γ-glutamylcysteine synthetase 117gastrointestinal tract 22, 35, 37, 41, 56gem-dimethyl 86

genetic polymorphism 79glomerular filtration rate 67, 127glomerular filtration 62glomerulus 67glucuronic acid 93glucuronidation 75, 90, 94glucuronyl transferase 62, 90, 91, 93glutathione conjugate 113, 115glutathione depletion 103glutathione transferase 102glutathione 93, 102glutathione-S-transferases 93glycine/NMDA antagonists 3G-protein coupled receptors 27, 47G-protein-coupled receptor antagonists 71griseofulvin 37

GSTs 93

h

haem iron 77haemolysis 112haemolytic anaemia 107half-life 17, 20, 24, 33dosing interval 20clearance 20volume of distribution 20halofantrine 37

haloperidol 28H-bonding 39, 40, 45, 48, 60, 136hepatic blood flow 129

hepatic clearance 60, 130hepatic extraction 19, 23blood flow 19hepatic impairment 56hepatic microsomes 128hepatic necrosis 103hepatic portal vein 22hepatic shunts 56hepatic uptake 60, 61, 131hepatitis 104

hepatocyte 60, 129, 138hepatotoxicity 102, 105high throughput permeability assessment 137

high throughput screening 133

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macrolide 54maximum absorbable dose 45maximum life span potential 128MDCK 44

melanin 48membrane barriers 2phospholipid bilayers 2membrane interactions 48membrane permeability 136membrane transfer 65membrane transport 137membrane 37

MetabolExpert 138metabolic clearance 63metabolic lability 39metabolism 65, 75, 137, 138conjugative 75

oxidative 75phase I 75phase II 75metabolite 138MetaFore 138metazosin 127Meteor 138methaemoglobinemia 112methyl transferase 92metiamide 114metoprolol 42, 51, 79mianserin 110microdialysis 50microsomal stability 129midazolam 23, 82, 124minoxidil 95molecular lipophilicity potential 10molecular modelling 138molecular size 45, 48molecular surface area 8absorption 8bile excretion 8molecular weight 43moricizine 118morphine 91, 95myeloperoxidase 106myosin 48

n

napsagatran 131N-dealkylation 82, 111

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PET scanning 28P-glycoprotein 41, 42, 43, 137pharmacokinetic modelling 139pharmacokinetic phase 26phase II conjugation 90phenacetin 104phenol 90, 91, 94phenolate anion 91phenytoin 37, 80, 103, 118, 128pholcodine 55

phospholipid 52, 54phospholipidosis 102physiological models 139physiological time 127pindolol 51

pirenzepine 30

pKa 136plasma protein binding 32, 69, 125, 129polar surface area 45, 136

polyethylene glycol 36polypharmacology 100poor absorption 23poor metabolizers 79practolol 106predictive methods 115pre-systemic metabolism 22procainamide 109

pro-drug design 43pro-drug 89pro-moiety 43propafenone 79propranolol 27, 38, 42, 51, 64, 88protein binding 137

proxicromil 102proximal tubule 67pulsed ultrafiltration-mass spectrometry 138

q

QSAR 115, 138quantitative structure-pharmacokinetic relationships 138

quantitiative structure-metabolism ships 138

relation-quinone imine 104, 111

r

radical stability 84Raevsky 40rash 106

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tacrine 105talinolol 42telenzepine 30tenidap 113teratogenicity 100, 103terfenadine 82tertiary amine 82thalidomide 100thioether adducts 109thiolate anion 93thiophene ring 112thiophene S-oxide 112thiophene 113thioridazine 28thiourea 114thromboxane A2receptor antagonists 61thromboxane receptor antagonists 130thromboxane synthase inhibitors 61ticlopidine 112

tienilic acid 112, 127tissue half-life 54

Tmax 56tocainide 109tolbutamide 80, 107, 127topical administration 88toxicity 99, 101, 102idiosyncratic 102metabolism 102pharmacology 99physiochemical properties 101structure 101

toxicogenomics 116toxicology 118toxicophore 108, 115transcellular diffusion 38transport proteins 41, 67, 69transport systems 60transporter proteins 129, 130, 137transporter 60, 61, 137

canalicular 60sinusoid 60triamterene 37triazole 72troglitazone 119tubular carrier systems 62tubular pH 69

tubular reabsorption 70, 72, 126tubular secretion 69, 70turbidimetry 136

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Index 149

u

UDP-α-glucuronic acid 90

unbound drug concentration 50

unbound drug 24, 125

GABA uptake inhibitors 6

histamine H1-receptor antagonists 6

uptake of drugs in the brain 6

tissue affinity 17total body water volume 17

w

water solubility 37white blood cell toxicity 113

z

zamifenacin 92, 126

96-well 137

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1

Physicochemistry

Abbreviations

3D-QSAR Three-dimensional quantitative structure–activity relationships

Symbols

log P Logarithm of the partition coefficient (P) of neutral species

log D Logarithm of the distribution coefficient (D) at a selected pH, usually

assumed to be measured in octanol/water

log Doct Logarithm of the distribution coefficient (D) at a selected pH, measured

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2 1 Physicochemistry

1.1

Physicochemistry and Pharmacokinetics

The body can be viewed as primarily composed of a series of membrane barriers viding aqueous filled compartments These membrane barriers are comprised prin-cipally of the phospholipid bilayers which surround cells and also form intracellularbarriers around the organelles present in cells (mitochondria, nucleus, etc.) Theseare formed with the polar ionized head groups of the phospholipid facing towardsthe aqueous phases and the lipid chains providing a highly hydrophobic inner core

di-To cross the hydrophobic inner core a molecule must also be hydrophobic and able

to shed its hydration sphere Many of the processes of drug disposition depend onthe ability or inability to cross membranes and hence there is a high correlation withmeasures of lipophilicity Moreover, many of the proteins involved in drug disposi-tion have hydrophobic binding sites further adding to the importance of the meas-ures of lipophilicity [1]

At this point it is appropriate to define the terms hydrophobicity and lipophilicity.According to recently published IUPAC recommendations both terms are best de-scribed as follows [2]:

Hydrophobicity is the association of non-polar groups or molecules in an aqueousenvironment which arises from the tendency of water to exclude non-polar mole-cules

Lipophilicity represents the affinity of a molecule or a moiety for a lipophilic ronment It is commonly measured by its distribution behaviour in a biphasic sys-tem, either liquid–liquid (e.g partition coefficient in 1-octanol/water) or solid–liquid(retention on reversed-phase high-performance liquid chromatography (RP-HPLC)

envi-or thin-layer chromatography (TLC) system)

The role of dissolution in the absorption process is further discussed in Section 3.2

1.2

Partition and Distribution Coefficient as Measures of Lipophilicity

The inner hydrophobic core of a membrane can be modelled by the use of an

organ-ic solvent Similarly a water or aqueous buffer can be used to mimorgan-ic the aqueousfilled compartment If the organic solvent is not miscible with water then a two-phase system can be used to study the relative preference of a compound for theaqueous (hydrophilic) or organic (hydrophobic, lipophilic) phase

For an organic compound, lipophilicity can be described in terms of its partition

coefficient P (or log P as it is generally expressed) This is defined as the ratio of

con-centrations of the compound at equilibrium between the organic and aqueous phases:

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1.2 Partition and Distribution Coefficient as Measures of Lipophilicity 3

The partition coefficient (log P) describes the intrinsic lipophilicity of the collection

of functional groups and carbon skeleton, which combine to make up the structure

of the compound, in the absence of dissociation or ionization Methods to measure

par-tition and distribution coefficients have been described [3, 4]

Every component of an organic compound has a defined lipophilicity and tion of partition coefficient can be performed from a designated structure Likewise,

calcula-the effect on log P of calcula-the introduction of a substituent group into a compound can be

predicted by a number of methods as pioneered by Hansch [5–8] (π values), Rekker

[9–10] (f values) and Leo/Hansch [5–7, 11–12] (f' values).

Partitioning of a compound between aqueous and lipid (organic) phases is anequilibrium process When in addition the compound is partly ionized in the aque-ous phase a further (ionization) equilibrium is set up, since it is assumed that undernormal conditions only the unionized form of the drug penetrates the organic phase[13] This traditional view is shown schematically in Figure 1.1 below However, thenature of the substituents surrounding the charged atom as well as the degree of de-localization of the charge may contribute to the stabilization of the ionic species andthus not fully exclude partitioning into an organic phase or membrane [14] An ex-ample of this is the design of acidic 4-hydroxyquinolones (Figure 1.2) as glycine/NMDA antagonists [15] Despite a formal negative charge these compounds appear

to behave considerable ability to cross the blood–brain barrier

In a study of the permeability of alfentanil and cimetidine through Caco-2 cells, amodel for oral absorption, it was deduced that at pH 5 about 60 % of the cimetidinetransport and 17 % of the alfentanil transport across Caco-2 monolayers can be at-tributed to the ionized form [16] (Figure 1.3) Thus the dogma that only neutralspecies can cross a membrane has been challenged recently

The intrinsic lipophilicity (P) of a compound refers only to the equilibrium of the

unionized drug between the aqueous phase and the organic phase It follows that the

Fig 1.1 Schematic depicting

the relationship between log P

and log D and pKa

Fig 1.2 4-Hydroxyquinolines with improved oral absorption

and blood–brain barrier permeability [15]

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remaining part of the overall equilibrium, i.e the concentration of ionized drug inthe aqueous phase, is also of great importance in the overall observed partition ratio

This in turn depends on the pH of the aqueous phase and the acidity or basicity (pKa)

of the charged function The overall ratio of drug, ionized and unionized, between

the phases has been described as the distribution coefficient (D), to distinguish it from the intrinsic lipophilicity (P) The term has become widely used in recent years to describe, in a single term the effective (or net) lipophilicity of a compound at a given pH

taking into account both its intrinsic lipophilicity and its degree of ionization The

distribution coefficient (D) for a monoprotic acid (HA) is defined as:

where [HA] and [A–] represent the concentrations of the acid in its unionized anddissociated (ionized) states respectively The ionization of the compound in water is

defined by its dissociation constant (Ka) as:

sometimes referred to as the Henderson–Hasselbach relationship Combination

of Eqs (1.1)–(1.3) gives the pH-distribution (or ‘pH-partition’) relationship:

For monoprotic organic bases (BH+dissociating to B) the corresponding ships are:

or

Fig 1.3 Transportation rate of basic drugs across Caco-2 monolayers:

alfentanil, rapid transport; cimetidine, slow transport [16]

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1.3 Limitations in the Use of 1-Octanol 5

From these equations it is possible to predict the effective lipophilicity (log D) of

an acidic or basic compound at any pH value The data required in order to use the

relationship in this way are the intrinsic lipophilicity (log P), the dissociation stant (pKa), and the pH of the aqueous phase The overall effect of these relationships

con-is the effective lipophilicity of a compound, at physiological pH, con-is the log P value minus one unit of lipophilicity, for every unit of pH the pKavalue is below (for acids)and above (for bases) pH 7.4 Obviously for compounds with multifunctional ioniz-

able groups the relationship between log P and log D, as well as log D as function of

pH become more complex [17] For diprotic molecules there are already 12 differentpossible shapes of log D–pH plots

1.3

Limitations in the Use of 1-Octanol

Octanol is the most widely used model of a biological membrane [18] and logD7.4ues above 0 normally correlate with effective transfer across the lipid core of themembrane, whilst values below 0 suggest an inability to traverse the hydrophobicbarrier

val-Octanol, however, supports H-bonding Besides the free hydroxyl group, octanolalso contains 4 % v/v water at equilibrium This obviously conflicts with the exclu-sion of water and H-bonding functionality at the inner hydrocarbon core of themembrane For compounds that contain functionality capable of forming H-bonds,therefore, the octanol value can over-represent the actual membrane crossing ability.These compounds can be thought of as having a high hydration potential and diffi-culty in shedding their water sphere

Use of a hydrocarbon solvent such as cyclohexane can discriminate these pounds either as the only measured value or as a value to be subtracted from the oc-tanol value (∆log P) [19–21] Unfortunately, cyclohexane is a poor solvent for manycompounds and does not have the utility of octanol Groups which hydrogen bondand attenuate actual membrane crossing compared to their predicted ability based

com-on octanol are listed in Figure 1.4 The presence of two or more amide, carboxylfunctions in a molecule will significantly impact on membrane crossing ability andwill need substantial intrinsic lipophilicity in other functions to provide sufficienthydrophobicity to penetrate the lipid core of the membrane

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1.4

Further Understanding of log P

1.4.1

Unravelling the Principal Contributions to log P

The concept that log P or log D is composed of two components [22], that of size and

polarity is a useful one This can be written as Eq (1.9),

where V is the molar volume of the compound, Λ a general polarity descriptor and

a is a regression coefficient Thus the size component will largely reflect the carbon

skeleton of the molecule (lipophilicity) whilst the polarity will reflect the hydrogenbonding capacity The positioning of these properties to the right and left of Figure1.4 reflects their influence on the overall physicochemical characteristics of a mole-cule

1.4.2

Hydrogen Bonding

Hydrogen bonding is now seen as an important property related to membrane meation Various scales have been developed [23] Some of these scales describe totalhydrogen bonding capability of a compound, while others discriminate betweendonors and acceptors [24] It has been demonstrated that most of these scales showconsiderable intercorrelation [25]

per-Lipophilicity and H-bonding are important parameters for uptake of drugs in thebrain [26] Their role has e.g been studied in a series of structurally diverse sedatingand non-sedating histamine H1-receptor antagonists [27] From these studies a deci-sion tree guideline for the development of non-sedative antihistamines was designed(see Figure 1.5)

GABA (γ-aminobutyric acid) is a major neurotransmitter in mammals and is volved in various CNS disorders In the design of a series of GABA uptake inhibitors

in-a lin-arge difference in in vivo in-activity between two compounds with identicin-al IC

val-Fig 1.4 Functionality and H-bonding

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1.4 Further Understanding of log P 7

ues was observed, one compound being devoid of activity [28] The compounds have

also nearly identical pKa and log Doctvalues (see Figure 1.6) and differ only in their

distribution coefficient in cyclohexane/water (log Dchex) This results in a ∆log D of

2.71 for the in vivo inactive compounds, which is believed to be too large for CNS

uptake The active compound has a ∆log D of 1.42, well below the critical limit ofapproximately 2 Besides this physicochemical explanation further evaluation ofmetabolic differences should complete this picture It should be noted that the con-cept of using the differences between solvent systems was originally developed forcompounds in their neutral state (∆log P values, see Section 2.2) In this case twozwitterions are being compared, which are considered at pH 7.4 to have a net zerocharge, and thus the ∆log P concept seems applicable

Fig 1.5 Decision tree for

the design of non-sedative

H1-antihistaminics Log D is

measured at pH 7.4, while

∆log P refers to compounds

in their neutral state (redrawn

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1.4.3

Molecular Size and Shape

Molar volume as used in Eq (1.9) is one way to express the size of a compound It isvery much related to molecular surface area For convenience often the molecularweight (MW) is taken as a first estimate of size It is also useful to realize that size isnot identical to shape

Many companies have tried to develop peptidic renin inhibitors Unfortunatelythese are rather large molecules and not unexpectedly poor absorption was often ob-served The role of physicochemical properties has been discussed for this class ofcompounds One of the conclusions was that compounds with higher lipophilicitywere better absorbed from the intestine [29] Absorption and bile elimination rate areboth MW-dependent Lower MW results in better absorption and less bile excretion.The combined influence of molecular size and lipophilicity on absorption of a series

of renin inhibitors can be seen from Figure 1.7 The observed iso-size curves are lieved to be part of a general sigmoidal relationship between permeability andlipophilicity [30–31] (for further details see Chapter 3)

be-1.5

Alternative Lipophilicity Scales

Since 1-octanol has certain limitations (see Section 1.3) many alternative

lipophilici-ty scales have been proposed (see Figure 1.8) A critical quartet of four solvent tems of octanol (amphiprotic), alkane (inert), chloroform (proton donor) and propy-

sys-Fig 1.7 Iso-molecular weight curves showing the influence of molecular

size on membrane permeability with increasing lipophilicity [32]

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1.6 Computational Approaches to Lipophilicity 9

lene glycol dipelargonate (PGDP) has been advocated [33–34] By measuring bution in all four, a full coverage of partitioning properties should be obtained Alsonon-aqueous systems such as heptane/acetonitrile [35] or heptane/glycol [36] may be

distri-of use This latter system appears to distri-offer a direct measure for hydrogen bonding Inorder to increase throughput over the traditional shake-flask and related methods,various chromatographic techniques can be used [1] Immobilized artificial mem-branes (IAM) in particular, have been given considerable attention [37, 38] IAMsconsist of phospholipids grafted onto a solid phase HPLC support intended to mim-

ic a membrane It appears that IAM retention times are highly correlated with shake

flask log D octanol/water coefficients and thus do not really measure anything new.

Along the same lines several groups have suggested that studying partitioning intoliposomes may produce relevant information related to membrane uptake and ab-sorption [38, 39]

1.6

Computational Approaches to Lipophilicity

In the design of new compounds as well as the design of experimental procedures an

a priori calculation log P or log D values may be very useful Methods may be based

on the summation of fragmental [40–42], or atomic contributions [43–45], or a bination [46, 47] Reviews on various methods can be found in references [40, 48–51].Further approaches based on the used of structural features have been suggested [48,

com-Fig 1.8 Experimental methods to measure lipophilicity (modified

after reference [23 ]) log Poct, 1-octanol/water partition coefficient;

log Pliposomes, partition coefficient between liposomes and buffer;

log Phexane, 1-hexane/water partition coefficient; logPPGDP, propyleneglycol dipelargonate/water partition coefficient; log

Pheptane/glycol, a non-aqueous partitioning system; SF, shake-flask;

pH-metric, log P determination based on potentiometric titration

in water and octanol/water; CPC, centrifugal partition graphy; RP-HPLC, reversed-phase high performance liquid chromatography; TLC, thin-layer chromatography; ODS, octa-decylsilane; ABZ, end-capped silica RP-18 column; ODP, octade-cylpolyvinyl packing; IAM, immobilized artificial membrane;

chromato-ILC, immobilized liposome chromatography; MEKC, micellar electrokinetic capillary chromatography

Trang 28

52] Atomic and fragmental methods suffer from the problem that not all tions may be parameterized This leads to the observation that for a typical pharma-ceutical file about 25 % of the compounds cannot be computed Recent efforts havetried to improve the “missing value” problem [53]

contribu-Molecular lipophilicity potential (MLP) has been developed as a tool in 3D-QSAR,for the visualization of lipophilicity distribution on a molecular surface and as an ad-ditional field in CoMFA studies [49] MLP can also be used to estimate conformation-

dependent log P values.

1.7

Membrane Systems to Study Drug Behaviour

In order to overcome the limitations of octanol other solvent systems have been gested Rather than a simple organic solvent, actual membrane systems have alsobeen utilized For instance the distribution of molecules has been studied betweenunilamellar vesicles of dimyristoylphosphatidylcholine and aqueous buffers Thesesystems allow the interaction of molecules to be studied within the whole membranewhich includes the charged polar head group area (hydrated) and the highlylipophilic carbon chain region Such studies indicate that for amine compounds ion-ized at physiological pH, partitioning into the membrane is highly favoured and in-dependent of the degree of ionization This is believed to be due to electrostatic in-teractions with the charged phospholipid head group This property is not shared

sug-Fig 1.9 Structures of chargeneutral (phosphatidylcholine)and acidic (phosphatidylser-ine) phospholipids togetherwith the moderately lipophilicand basic drug chlorphenter-mine The groupings R1 andR2 refer to the acyl chains ofthe lipid portions

Trang 29

1.7 Membrane Systems to Study Drug Behaviour 11

with acidic compounds even for the “electronically neutral” phosphatidylcholine [54].Such ionic interactions between basic drugs are even more favoured for membranescontaining “acidic” phospholipids such as phosphatidylserine [55] The structures ofthese two phospholipids are shown in Figure 1.9 below together with the structure ofthe basic drug chlorphentermine

Table 1.1 shows the preferential binding of chlorphentermine to choline-containing membranes, the phospholipid with overall acidic charge Thesesystems predict the actual affinity of the compound for the membrane, rather thanits ability to cross the membrane Membrane affinity, and hence tissue affinity, isparticularly important in the persistence of drugs within the body, a topic which will

phosphatidyl-be covered in Section 4.2

Tab 1.1: Affinity (k) and capacity (moles drug/moles lipid) of

chlorphentermine for liposomes prepared from choline and phosphatidylserine

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2

Pharmacokinetics

Abbreviations

Symbols

Trang 33

16 2 Pharmacokinetics

log D7.4 Distribution coefficient (octanol/buffer) at pH 7.4

pA2 Affinity of antagonist for a receptor (= – log10[KB])

2.1

Setting the Scene

Pharmacokinetics is the study of the time course of a drug within the body and corporates the processes of absorption, distribution, metabolism and excretion(ADME) In general, pharmacokinetic parameters are derived from the measure-ment of drug concentrations in blood or plasma The simplest pharmacokinetic con-cept is that based on total drug in plasma However, drug molecules may be bound

in-to a greater or lesser extent in-to the proteins present within the plasma, thus free druglevels may be vastly different from those of total drug levels Blood or plasma are thetraditionally sampled matrices due to (a) convenience and (b) to the fact that the con-centrations in the circulation will be in some form of equilibrium with the tissues ofthe body Because of analytical difficulties (separation, sensitivity) it is usually the to-tal drug that is measured and used in pharmacokinetic evaluation Such measure-ments and analysis are adequate for understanding a single drug in a single species

in a number of different situations since both protein binding and the resultant bound fraction are approximately constant under these conditions When species or

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un-2.2 Intravenous Administration: Volume of Distribution 17

drugs are compared, certain difficulties arise in the use of total drug and unbound(free) drug is a more useful measure (see below)

2.2

Intravenous Administration: Volume of Distribution

When a drug is administered intravenously into the circulation the compound dergoes distribution into tissues etc and clearance For a drug that undergoes rapiddistribution a simple model can explain the three important pharmacokinetic terms:volume of distribution, clearance and half-life

un-Volume of distribution (Vd) is a theoretical concept that connects the administered dose with the actual initial concentration (C0) present in the circulation The rela-tionship is shown below:

For a drug that is confined solely to the circulation (blood volume is 80 mL kg–1)the volume of distribution will be 0.08 L kg–1 Distribution into total body water(800 mL kg–1) results in a volume of distribution of 0.8 L kg–1 Beyond these valuesthe number has only a mathematical importance For instance a volume of distribu-tion of 2 L kg–1means only, that less than 5 % of the drug is present in the circula-tion The drug may be generally distributed to many tissues and organs or concen-trated in only a few

For different molecules, the apparent volume of distribution may range fromabout 0.04 L kg–1to more than 20 L kg–1 High molecular weight dyes, such as indo-cyanine green, are restricted to the circulating plasma after intravenous administra-tion and thus exhibit a volume of distribution of about 0.04 L kg–1 For this reasonsuch compounds are used to estimate plasma volume [1] and hepatic blood flow [2].Certain ions, such as chloride and bromide, rapidly distribute throughout extracellu-lar fluid, but do not readily cross cell membranes and therefore exhibit a volume ofdistribution of about 0.4 L kg–1which is equivalent to the extracellular water volume[3] Neutral lipid-soluble substances can distribute rapidly throughout intracellularand extracellular water For this reason antipyrine has been used as a marker of totalbody water volume and exhibits a volume of distribution of about 0.7 L kg–1[4] Com-pounds which bind more favourably to tissue proteins than to plasma proteins canexhibit apparent volumes of distribution far in excess of the body water volume This

is because the apparent volume is dependent on the ratio of free drug fractions in theplasma and tissue compartments [5] High tissue affinity is most commonly ob-served with basic drugs and can lead to apparent volumes of distribution up to

21 L kg–1for the primary amine-containing calcium channel blocker, amlodipine [6]

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2.3

Intravenous Administration: Clearance

Clearance of drug occurs by the perfusion of blood to the organs of extraction

Ex-traction (E) refers to the proportion of drug presented to the organ which is removed

irreversibly (excreted) or altered to a different chemical form (metabolism)

Clear-ance (Cl) is therefore related to the flow of blood through the organ (Q) and is

ex-pressed by the formula:

The organs of extraction are generally the liver (hepatic clearance – metabolismand biliary excretion; ClH) and the kidney (renal excretion, ClR) and the values can besummed together to give an overall value for systemic clearance (ClS):

Extraction is the ratio of the clearance process compared to the overall ance of the compound from the organ The clearance process is termed intrinsicclearance Cli, the other component of disappearance is the blood flow (Q) from the

disappear-organ This is shown in Figure 2.1 below

Combining Eqs (2.2) and (2.3) with the scheme in Figure 2.1 gives the generalequation for clearance:

Where Cl = ClSif only one organ is involved in drug clearance Within this tion Cliis the intrinsic clearance based on total drug concentrations and therefore in-cludes drug bound to protein Lipophilic drugs bind to the constituents of plasma(principally albumin) and in some cases to erythrocytes It is a major assumption,supported by a considerable amount of experimental data, that only the unbound(free) drug can be cleared The intrinsic clearance (Cli) can be further defined as:

Where Cliuis the intrinsic clearance of free drug, i e unrestricted by either flow or

binding, and fuis the fraction of drug unbound in blood or plasma

Inspection of the above equation indicates for compounds with low intrinsic

clear-ance compared to blood flow, Q and (Cli+ Q) effectively cancel and Cl (or ClS) proximates to Cl Conversely, when intrinsic clearance is high relative to blood flow,

ap-Fig 2.1 Schematic illustrating hepatic tion with Q, blood flow and Cli, intrinsic clear-ance (metabolism)

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extrac-2.4 Intravenous Administration: Clearance and Half-life 19

Cliand (Cli+ Q) effectively cancel and Cl (or ClS) is equal to blood flow (Q) The

im-plications of this on drugs cleared by metabolism is that the systemic clearance oflow clearance drugs are sensitive to changes in metabolism rate whereas that of highclearance drugs are sensitive to changes in blood flow

It is important to recognize the distinction between the various terms used fordrug clearance and the inter-relationship between these Essentially intrinsic clear-ance values are independent of flow through the organ of clearance, whilst unboundclearance terms are independent of binding These relationships are illustrated inFigure 2.2

2.4

Intravenous Administration: Clearance and Half-life

Clearance is related to the concentrations present in blood after administration of adrug by the equation:

where AUC is the area under the plasma concentration time curve Clearance is aconstant with units often given as mL min–1or mL min–1kg–1body weight Thesevalues refer to the volume of blood totally cleared of drug per unit time Hepaticblood flow values are 100, 50 and 25 mL min–1kg–1in rat, dog and man respectively.Blood clearance values approaching these indicate that hepatic extraction is very high(rapid metabolism)

Blood arriving at an organ of extraction normally contains only a fraction of the tal drug present in the body The flow through the major extraction organs, the liverand kidneys, is about 3 % of the total blood volume per minute, however, for many

to-Fig 2.2 Inter-relationship

between various terms of drug

clearance used within

pharma-cokinetic analysis

Trang 37

drugs, distribution out of the blood into the tissues will have occurred The duration

of the drug in the body is therefore the relationship between the clearance (bloodflow through the organs of extraction and their extraction efficiency) and the amount

of the dose of drug actually in the circulation (blood) The amount of drug in the culation is related to the volume of distribution and therefore to the elimination rate

cir-constant (kel) which is given by the relationship:

2.5

Intravenous Administration: Infusion

With linear kinetics, providing an intravenous infusion is maintained long enough,

a situation will arise when the rate of drug infused = rate of drug eliminated The

FFiigg 22 33 Effect of clearanceand volume of distribution onhalf-life for a simple singlecompartment pharmacokineticmodel

Trang 38

plasma or blood concentrations will remain constant and be described as “steadystate” The plasma concentration profile following intravenous infusion is illustrated

Thus the time taken to reach steady state is dependent on kel The larger kel

(short-er the half-life) the more rapidly the drug will attain steady state As a guide 87 % ofsteady state is attained when a drug is infused for a period equal to three half-lives.Decline from steady state will be as described above, so a short half-life drug will rap-idly attain steady state during infusion and rapidly disappear following the cessation

Fig 2.5 Intravenous infusion

with infusion rate doubled

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Increasing the infusion rate will mean the concentrations will climb until a newsteady state value is obtained Thus doubling the infusion rate doubles the steadystate plasma concentration as illustrated in Figure 2.5

2.6

Oral Administration

When a drug is administered orally, it has to be absorbed across the membranes ofthe gastrointestinal tract Incomplete absorption lowers the proportion of the doseable to reach the systemic circulation The blood supply to the gastrointestinal tract(GIT) is drained via the hepatic portal vein which passes through the liver on its pas-sage back to the heart and lungs Transport of the drug from the gastrointestinaltract to the systemic circulation will mean the entire absorbed dose has to passthrough the liver

On this “first-pass” the entire dose is subjected to liver extraction and the fraction

of the dose reaching the systemic circulation (F) can be substantially reduced (even

for completely absorbed drugs) as shown in the following equation:

Again E is the same concept as that shown in Figure 2.1 This phenomenon is

termed the first-pass effect, or psystemic metabolism, and is a major factor in ducing the bioavailability of lipophilic drugs From the concept of extraction shown

re-in Figure 2.1, rapidly metabolized drugs, with high Clivalues, will have high tion and high first-pass effects An example of this type of drug is the lipophilic cal-cium channel blocker, felodipine This compound has an hepatic extraction of about0.80, leading to oral systemic drug exposure (AUC) of only about one-fifth of that ob-served after intravenous administration [7] Conversely, slowly metabolized drugs,with low Clivalues, will have low extraction and show small and insignificant first-pass effects The class III anti-dysrhythmic drug, dofetilide, provides such an exam-ple Hepatic extraction of this compound is only about 0.07, leading to similar sys-temic exposure (AUC) after oral and intravenous doses [8]

extrac-Fig 2.6 Schematic illustratingthe disposition of a drug afteroral administration

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2.7 Repeated Doses 23

A complication of this can be additional first-pass effects caused by metabolism bythe gastrointestinal tract itself In the most extreme cases, such as midazolam, ex-traction by the gut wall may be as high as 0.38 to 0.54 and comparable to that of theliver itself [9]

The previous equations referring to intravenously administered drugs (e g

Eq 2.6) can be modified to apply to the oral situation:

Where Clois the oral clearance and F indicates the fraction absorbed and escaping

hepatic first-pass effects Referring back to the intravenous equation we can calculate

F or absolute bioavailability by administering a drug intravenously and orally and

measuring drug concentrations to derive the respective AUCs When the same dose

of drug is given then:

The estimation of systemic clearance together with this value gives valuable mation about the behaviour of a drug High clearance drugs with values approachinghepatic blood flow will indicate hepatic extraction (metabolism) as a reason for lowbioavailability In contrast poor absorption will probably be the problem in low clear-ance drugs which show low bioavailabilities

infor-2.7

Repeated Doses

When oral doses are administered far apart in time they behave independently This

is usually not the desired profile if we assume that a certain concentration is needed

to maintain efficacy and if a certain concentration is exceeded side-effects will occur.Giving doses of the drug sufficiently close together so that the following doses areadministered prior to the full elimination of the preceding dose means that some ac-cumulation will occur, moreover a smoothing out of the plasma concentration pro-file will occur This is illustrated in Figure 2.7

Fig 2.7 Plasma concentration

profile for multiple oral dose

administration

Tiêu đề	Pharmacokinetics and Metabolism in Drug Design
Tác giả	Dennis A. Smith, Han van de Waterbeemd, Don K. Walker
Trường học	Heinrich Heine University Düsseldorf
Chuyên ngành	Pharmacokinetics and Metabolism in Drug Design
Thể loại	Sách giáo trình
Năm xuất bản	2001
Thành phố	Düsseldorf

Định dạng
Số trang	155
Dung lượng	2,02 MB